Estimating citation gaps by team size: Evidence from a cross-disciplinary analysis

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Authors: Hwiyoung P. Lee, Chelsea Zhang, Manuel S. González Canché, Yoosun Park, Ram A. Cnaan
Cited by: 2
References: 46

Abstract

Citations in academia, once a respectful nod to intellectual predecessors, have become central metrics of influence, achievement, and recognition, particularly within elite academic circles. As collaborative research becomes more prevalent, shifting authorship dynamics raise questions about how solo and small-team contributions are valued in a system increasingly oriented toward multi-author publications. Although prior work documents a positive association between team size and citation outcomes, few studies quantify the magnitude of this relationship with sufficient granularity or assess how it varies across disciplines. Using Scopus bibliometric data, we analyze 417,201 English-language articles published in 2014 across eight disciplines—four in the social sciences (economics, education, social work, sociology) and four in STEM (bioengineering, chemistry, computer science, physics)—controlling for detailed article- and journal-level characteristics, including journal fixed effects. We find that solo-authored papers consistently receive fewer citations and that larger teams are generally associated with higher citation counts. Across both social sciences and STEM, the citation gap between solo- and multi-authored articles typically ranges from 0.1 to 0.2 standard deviations per article. The shape of the relationship differs by field: in the social sciences, returns to coauthorship follow an inverted-U, whereas in STEM fields, citations tend to increase more steadily with team size. These field-specific estimates can inform the development and fine-tuning of evaluation metrics, helping build more robust assessment frameworks.

Fields of Study & Subjects

scientometrics and bibliometrics research Academic Writing and Publishing Interdisciplinary Research and Collaboration

Publication details

Journal / source
Journal of Informetrics
Publisher
Elsevier BV
Volume
20
Issue
1
Pages
101780–101780
Publication date
11 February 2026
Language
EN